code: def test_cpu_adam_gpu_error():
      model_size = 64
      from deepspeed.ops.adam import DeepSpeedCPUAdam
  
      device = "cuda:0"
      param = torch.nn.Parameter(torch.randn(model_size, device=device))
      optimizer = DeepSpeedCPUAdam([param])
  
      param.grad = torch.randn(model_size, device=device)
      with pytest.raises(AssertionError):
          optimizer.step()
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/tests/unit/ops/adam/test_cpu_adam.py
imports: import torch
  import numpy
  import pytest
  from cpuinfo import get_cpu_info
  import deepspeed
  from deepspeed.ops.adam import FusedAdam
  from deepspeed.ops.op_builder import CPUAdamBuilder
label_desc: Use image node_id 3 for calling a global function with example usage: test_cpu_adam_gpu_error() without return types